Non-stationarities in the relationships of heavy precipitation events in the Mediterranean area and the large-scale circulation in the second half of the 20th century

Abstract

In the context of analyzing temporal varying relationships of heavy precipitation events in the Mediterranean area and associated anomalies of the large-scale circulation, quantile regression models were established. The models were calibrated using different circulation and thermodynamic variables at the 700hPa and 850hPa levels as predictors as well as daily precipitation time series at different stations in the Mediterranean area as predictand. Analyses were done for the second half of the 20th century. In the scope of assessing non-stationarities in the predictor-predictand relationships the time series were divided into calibration and validation periods. 100 randomized subsamples were used to calibrate/validate the models under stationary conditions. The highest and lowest skill score of the 100 random samples was used to determine the range of random variability. The model performance under non-stationary conditions was derived from the skill scores of cross-validated running subintervals. If the skill scores of several consecutive years are outside the range of random variability a non-stationarity was declaimed. Particularly the Iberian Peninsula and the Levant region were affected by non-stationarities, the former with significant positive deviations of the skill scores, the latter with significant negative deviations. By means of a case study for the Levant region we determined three possible reasons for non-stationary behavior in the predictor-predictand relationships. The Mediterranean Oscillation as a superordinate system affects the cyclone activity in the Mediterranean basin and the location and intensity of the Cyprus low. Overall, it is demonstrated that non-stationarities have to be taken into account within statistical downscaling model development.